As someone in the AI field, I wanted to share some of my thoughts on these two AI centric companies. I just started a small position in Upstart this week and have a slightly larger position in Crowdstrike. This post only covers the barriers to entry from a technical standpoint and not the business aspects, first mover advantage etc.
Crowdstrike AI - Crowdstrike provides an unique ability to learn from all threats vs. their on-prem competitors. This is critical, once a threat is detected in one customer, all customers are protected and that clearly provides a far superior outcome. You can easily imagine customers wanting that, willing to pay a premium etc. When designing an AI system, some key factors need to be taken into account - model complexity, value of additional data and domain expertise (these form the barriers of entry). For security threats, you deal with a class of models that have extremely high data imbalance (normal events far outweigh threats). This makes every new incremental threat detected very valuable and the model continues to improve with more data for a long period of time. Security is also a complex field and significant domain expertise is required to build a sophisticated AI model. I think you get the picture, Crowdstrike AI is a complicated beast that’ll just keep getting better and better. Their early lead created a virtuous cycle (better AI->more customers->more data->more threats detected->better AI) and that gives them an impenetrable moat.
Upstart AI - The core principles are the same as Crowdstrike, build an AI system that gets better over time. Now let’s look at key factors - this’ll be a fairly straightforward model (relatively speaking). More data is good and the model can learn new patterns / behaviors, but there’s a point of diminishing returns (unlike security threats, the various flavors you could have here are limited). On domain expertise, no doubt you’ll have underwriters with in depth understanding of the personal credit market and they bring a level of sophistication to the model with their knowledge. But it wouldn’t be that hard for even a layman to quickly grasp the key factors that influence small personal loans. More importantly, most of their customers being banks will already have this expertise. In my opinion, it’ll only take a small team to build this model. Most banks already have their own machine learning teams (especially the big ones) and they might quickly come to the same conclusion. Upstart’s AI definitely has a legup in that it’ll learn from data from multiple banks, but that advantage (as it relates to model performance) doesn’t provide a large enough moat. To summarize, it’s not clear to me there are significant barriers to entry purely from a technical / AI standpoint here.
Hope this helps.